This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
Increasingly, models of the world are directly built from images. The paper discusses a number of recent developments that try to push the enveloppe of what image-based modeling c...
Luc J. Van Gool, D. Vandemeulen, Gregor A. Kalbere...
Over the past few years, some embedding methods have been proposed for feature extraction and dimensionality reduction in various machine learning and pattern classification tasks...
In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequenc...
In this paper, we introduce a novel real-time tracker based on color, texture and motion information. RGB color histogram and correlogram (autocorrelogram) are exploited as color ...